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Data-driven approach for port resilience evaluation

Author

Listed:
  • Gu, Bingmei
  • Liu, Jiaguo
  • Ye, Xiaoheng
  • Gong, Yu
  • Chen, Jihong

Abstract

As pivotal nodes in international trade, ports have faced unprecedented challenges, particularly in the context of the COVID-19 pandemic. From the perspective of port congestion, this study investigates port resilience based on a quantitative approach. Port resilience is specifically evaluated using five novel metrics derived from resilience capacities and port congestion indexes, employing data-driven approaches, which are then applied to analyze nine global ports across six regions. The findings of the study indicate that: 1) The ports of Southampton and Shanghai display better resilience levels, whereas New York/New Jersey and Los Angeles/Long Beach show poorer resilience performance during the research period. 2) Ports in West Coast North America demonstrate relatively low resilience levels, while those in South East Asia showcase superior resilience. 3) The changing dynamics and evolution of port resilience rankings across different years underscore the multifaceted nature of port resilience and its capacity to adapt to external factors such as global events. Our study emphasizes the importance of quantifying port resilience, with a specific focus on port congestion. It provides valuable insights that have significant implications for port management and disaster preparedness within the maritime industry.

Suggested Citation

  • Gu, Bingmei & Liu, Jiaguo & Ye, Xiaoheng & Gong, Yu & Chen, Jihong, 2024. "Data-driven approach for port resilience evaluation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
  • Handle: RePEc:eee:transe:v:186:y:2024:i:c:s1366554524001613
    DOI: 10.1016/j.tre.2024.103570
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    6. Zhao, Yulan & Ma, Xiaoxue & Qiao, Weiliang & Zhang, Jianqi, 2025. "Resilient maritime transportation system from the perspective of FRAM: conceptualization and assessment," Reliability Engineering and System Safety, Elsevier, vol. 262(C).
    7. Lu, Bo & Sun, Yue & Wang, Huipo & Wang, Jian-Jun & Shuai Liu, Samuel & Cheng, T.C.E., 2024. "Dynamic resilience analysis of the liner shipping network: From structure to cooperative mechanism," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 191(C).
    8. Xing, Zheng & Zhou, Chenhao & Shen, Yu & Chew, Ek Peng & Tan, Kok Choon, 2026. "Optimizing port system resilience through integrated preparedness and recovery strategies," Reliability Engineering and System Safety, Elsevier, vol. 266(PB).

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